MST 011 Real Analysis, Calculus and Geometry | IN-DEPTH STUDY GUID for IGNOU 
MST 011 Real Analysis, Calculus and Geometry | IN-DEPTH STUDY GUIDE for IGNOU 
MST 012 Probability and Probability Distributions | IN-DEPTH STUDY GUIDE for IGNOU 
MST 013 Survey Sampling and Design of Experiments-I | IN-DEPTH STUDY GUIDE for IGNOU 
MST 014 Statistical Quality Control and Time Series Analysis | IN-DEPTH STUDY GUIDE for IGNOU 
MST 015 Introduction to R Software | IN-DEPTH STUDY GUIDE for IGNOU 
MST 016 Statistical Inference| IN-DEPTH STUDY GUIDE for IGNOU 
MST 017 Applied Regression Analysis | IN-DEPTH STUDY GUIDE for IGNOU 
MST 018 Multivariate Analysis | IN-DEPTH STUDY GUIDE for IGNOU 
MST 019 Epidemiology and Clinical Trials | IN-DEPTH STUDY GUIDE for IGNOU 
MST 020 Survey Sampling and Design of Experiments-II| IN-DEPTH STUDY GUIDE for IGNOU 
MST 021 Classical and Bayesian Inference | IN-DEPTH STUDY GUIDE for IGNOU 
MST 022 Linear Algebra and Multivariate Calculus | IN-DEPTH STUDY GUIDE for IGNOU 
MST 023 Research Methodology | IN-DEPTH STUDY GUIDE for IGNOU 
MST 024 Data Analysis with Python | IN-DEPTH STUDY GUIDE for IGNOU 
MST 025 Categorical and Survival Analysis | IN-DEPTH STUDY GUIDE for IGNOU 
MST 026 Introduction to Machine Learning | IN-DEPTH STUDY GUIDE for IGNOU 
MSTE 012 Stochastic Processes | IN-DEPTH STUDY GUIDE for IGNOU 
MSTE 011 Operations Research | Quick Readable...
Rs.149
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| Category | : MASTER‘S DEGREE PROGRAMMES |
| Sub Category | : Master of Science (Applied Statistics) (MSCAST) |
| Products Code | : MSCAST-MST-S4-5.51 |
| HSN Code | : 490110 |
| Language | : English |
| Author | : BMAP EDUSERVICES PVT LTD |
| Publisher | : BMAP EDUSERVICES PVT LTD |
| University | : IGNOU (Indira Gandhi National Open University) |
| Pages | : 300 |
| Weight | : 199 GM |
| Dimensions | : 21.0 x 29.7 cm (A4 Size Pages) |
MSTE 011 Operations Research is designed to provide students with a robust understanding of analytical methods used to improve decision-making processes. This course covers a range of topics including linear programming, optimization techniques, queuing theory, inventory models, and simulation techniques. It equips students with the skills necessary to apply these methods to complex real-world problems.
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